We found that at least some expression in tumor cells was seen in 97% of cases for HVEM, 83% for PD-L1, 79% for Gal-9 and 66% for IDO. In the discovery cohort (n = 94), we found that lack of, or low, tumor expression of PD-L1 (p < 0.001), Galectin-9 (p < 0.001) and HVEM (p < 0.001), and low CD8+TIL count (p = 0.016), were associated with poor HCC-specific survival. PD-L1, Galectin-9 and CD8+TIL count were predictive of HCC-specific survival independent of baseline clinicopathologic characteristics and the combination of these markers was a powerful predictor of HCC-specific survival . These results were confirmed in the validation cohort (n = 60). We show that low expression levels of PD-L1 and Gal-9 in combination with low CD8+TIL count predict extremely poor HCC-specific survival and it requires a change in two of these parameters to significantly improve prognosis. In conclusion, intra-tumoral expression of these immune inhibiting molecules was observed in the majority of HCC patients. Low expression of PD-L1 and Galectin-9 and low CD8+TIL count are associated with poor HCC-specific survival. Combining immune biomarkers leads to superior predictors of HCC mortality.Novel systemic treatments for hepatocellular carcinoma (HCC) are strongly needed. Immunotherapy is a promising strategy that can induce specific antitumor immune responses. Understanding the mechanisms of immune resistance by HCC is crucial for development of suitable immunotherapeutics. We used immunohistochemistry on tissue-microarrays to examine the co-expression of the immune inhibiting molecules PD-L1, Galectin-9, HVEM and IDO, as well as tumor CD8 AFPα fetoproteinAMCAmsterdam Medical CenterEMCErasmus MC-University Medical CenterGal-9galectin-9HCChepatocellular carcinomaTFLtumor-free liverTILtumor-infiltrating lymphocytesTMAtissue microarrayHepatocellular carcinoma (HCC) is a leading cause of cancer-related death.Immunotherapeutic strategies, such as tumor vaccination, adoptive cell therapy and immune modulating antibodies, may provide alternative therapeutic options in HCC.in-vitro abrogation of the PD-1/PD-L1 interaction has been shown to reinvigorate tumor-specific responses of T-cells isolated from HCC patients.Binding of PD-L1 to its receptor PD-1, on activated T cells, suppresses T-cell responses.As clinical efficacy of immune checkpoint antibodies seems dependent on expression of their target molecules in tumorsArchived formalin fixed paraffin-embedded tissue samples from 154 patients who underwent hepatic resection for HCC at Erasmus MC-University Medical Center  or Amsterdam Medical Center , between June 2001 and July 2014, were used for this study. Fresh frozen tissue, which was available from 20 additional patients, was used for RNA extraction. Patients with HCC were selected for the study if they had undergone surgery with curative intent. Clinical information was collected retrospectively from the electronic record. The clinical information collected included etiologic factors, HCC recurrence, patient death, cause of death, as well as known prognostic clinicopathologic characteristics, such as tumor differentiation, vascular invasion, number of lesions, largest tumor size and pre-surgical α-fetoprotein (AFP) level. The study was approved by the local medical ethical committee. In addition, the study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki.Three or four 0.6 mm cores were taken from the tumorous area of 154 patients and two 0.6 mm cores were taken from the corresponding tumor-free liver (TFL) area of 133 of these patients. Areas with vital tumor and TFL tissue were marked by experienced pathologists (KB or JV) using archived H&E glass slides. The TMAs were made using either an automated tissue-arrayer ATA-27  or a fully manual tissue-arrayer MTA-1 (Beecher Instruments).+ staining, the positive cells per core were counted manually and average counts were used for analysis.Complete information on the immunohistochemistry protocols can be found in the supplementary methods section. Complete information on the primary antibodies used can be found in Table S1. Scoring was performed by two independent investigators (KS and HS) blinded to clinical outcome and differences resolved by mutual agreement. Scoring was performed on cancer cells (tumor cores) or hepatocytes (TFL cores). Intensity was scored in a scale from zero to three. Intra-core heterogeneity of staining intensity of tumor cells or hepatocytes was rarely observed in our cohort, thus only staining intensity was taken into consideration. In the case of CD8All primers for the target genes were intron spanning and sequences are listed in Table S2. The RT-PCR amplification technique and primer sources are described in detail in the supplementary methods section.T-test. The associations between clinicopathologic parameters with the expression of immune inhibitory molecules, as well as the co-expression of the immune inhibiting molecules with each other, were examined using the χ2 tests or the T-test as appropriate. Survival  was calculated from the date of surgery to the date of event , or the date of last follow-up. Patients lost to follow-up were censored as of the last day of follow-up. Patients who died from causes other than HCC were censored at the date of death. Survival curves were estimated by the Kaplan-Meier method. For sensitivity analysis, the survival analysis was repeated by excluding the patients who died from post-surgical complications within 3 mo after surgery. Optimal high vs. low values were established by examining a grid of cutoffs and choosing the cutoff with the lowest −2 log likelihood, taking into consideration to maximize the proportion of patients identified by the cutoff value when possible. The Breslow test was used to asses differences between survival curves of different groups, while for parameters with three or four linearly associated levels the linear trend for factor levels was used. Given that we examined the expression of five individual parameters  Bonferroni's correction required a p-value of < 0.01 for statistical significance in the discovery cohort. For multivariate analysis, the Cox proportional Hazard regression analysis was used. The statistical analysis was performed using the SPSS© 21 software.All analysis was performed in duplicate. The discovery phase was performed in the EMC cohort while the validation phase was performed in the AMC cohort. The differences in expression of immune inhibitory molecules between tumor and TFL tissue was analyzed with the paired −1 (p = 0.002), multiple lesions (p = 0.043) and tumor size >3 cm (p = 0.024) were associated with poor HCC-specific survival in the combined cohort . Tumor grade and vascular invasion were not associated with HCC-specific survival.Clinicopathologic characteristics of patients in the EMC discovery cohort and the AMC validation cohort can be seen in p < 0.001), Gal-9 (p < 0.001) and HVEM (p < 0.001) was associated with poor HCC-specific survival, while expression of IDO was not associated with HCC-specific survival (p = 0.953). Hazard ratios and 95% confidence intervals can be found in +TIL. The relationship of CD8+TIL count with HCC-specific survival was not significant after Bonferroni's correction (p = 0.016). For HCC recurrence the relationship with expression of these molecules followed the same trends . Low tumor expression of PD-L1 (p < 0.001), Gal-9 (p = 0.009), HVEM (p = 0.004), and also low CD8+TIL count (p = 0.007) were significantly associated with shorter time to HCC recurrence, while tumor expression of IDO was not associated with recurrence after Bonferroni's correction (p = 0.029). The results did not differ when analyses was performed by excluding the nine patients who died at EMC in the post-surgical period from causes other than HCC.Next, we investigated the relationship between immune inhibitory molecule expression and survival in the EMC cohort. Optimal cut-offs for low versus high staining were made as described in the statistical methods. Patients were considered to have low PD-L1 (n = 16) or Gal-9 (n = 18) staining when there was complete absence of staining, while low HVEM included patients with either complete absence of staining or very faint staining (n = 9). Low IDO (n = 63) included patients with complete absence, or at most +1, staining intensity. We found that expression in tumor tissue, but not in surrounding TFL tissue, was significantly associated with HCC-specific survival for three out of the four molecules examined . Specifip values < 0.02 were entered in a single model, we derived that tumor expression of PD-L1, Gal-9, CD8+TIL count, AFP level and number of lesions were independent predictors of HCC-specific survival in the EMC cohort .Because of the ability of the immune inhibitory molecules to predict HCC-specific survival, we wondered whether combining all three independently prognostic immune parameters would improve the prediction. p = 0.010) and Gal-9 (p = 0.047) were also significantly associated with poor HCC-specific survival , with a hazard ratio  that was of similar magnitude and direction as in the discovery (EMC) cohort . The combination of PD-L1, Gal-9 and CD8+TIL as a single biomarker  and was validated as an independent predictor of HCC-specific survival in multivariate analysis in the AMC cohort (p = 0.005).External validation of the above findings was performed in the cohort from AMC. Low tumor expression of PD-L1  but not with Gal-9, HVEM or IDO. Specifically, high expression of PD-L1 was correlated with a high CD8+TIL count and vice-versa.Low levels of expression of either PD-L1, Gal-9 or HVEM were significantly associated with low levels of expression of the other two ligands (Table S6). Such a relationship was not seen with IDO. The CD8+TIL count is associated with very poor HCC-specific survival, while high PD-L1 and high CD8+TIL count is associated with good HCC-specific survival . The presence of either high PD-L1 or high CD8+TIL count alone is associated with intermediate survival. A similar observation was made for the combination of Gal-9 tumor expression and CD8+TIL count   .Figure +TIL count, are independent predictors of poor HCC-specific survival. HVEM expression, on the other hand, while individually an independent predictor of HCC-specific survival, was not independent when other immune parameters were taken into consideration. The combination of tumor PD-L1 and Gal-9 expression and CD8+TIL count appeared to be a powerful independent predictor of HCC-specific survival. We show that there is a group of patients with extremely poor prognosis who express low levels of PD-L1 and Gal-9 and have low CD8+TIL count. It requires a change in two of these parameters to significantly affect prognosis.In two independent cohorts, we found that low tumor expression of PD-L1 and Gal-9, as well as low CD8Similar to our results, low expression of PD-L1 was found to be associated with poor survival in melanoma,Regarding the prognostic significance of Gal-9 expression in tumors there is more consensus. Similar to our findings, under-expression of Gal-9 has been associated with poor outcome in HCC,One may wonder why low expression of these molecules signifies high risk of HCC death, since their expression in itself is supposed to inhibit effector immune responses. It is known that several of these molecules are overexpressed in response to IFNγ and TIL infiltration, a process called adaptive immune resistance.+TIL infiltration (type II tumors), which suggests tumors with immune ignorance, according to the model by Teng et al.,Several studies have shown that expression of PD-L1 is associated with TIL infiltration in various cancers.While the tumor expression status of these molecules in HCC has been reported, the expression of these molecules in the surrounding TFL tissue is much less understood. While PD-L1 and IDO have been shown, in single studies, to be indeed expressed in TFL tissue of patients with HCC,+ lymphocytes are abundant, FoxP3+ T-regulatory cells are much less common and thus more difficult to systematically evaluate using TMAs.In our opinion, our study has several strong characteristics. We have studied a homogenous group of patients, have studied the expression of multiple immune inhibitory molecules in tumor, as well as surrounding TFL, tissue and have validated our findings in an independent cohort. Our study is the first to examine the co-expression of multiple immune inhibitory molecules in HCC. There are of course also limitations in our study. Our selected panel of immune inhibitory molecules is by no means exhaustive. We focused on molecules for which there is solid evidence for their immune inhibitory role in cancer, for which a reliable antibody was available for immunohistochemistry and for which the corresponding mechanism of interaction with immune cells is well understood. However, as our understanding of the immune inhibiting mechanisms of cancer expands other molecules should be added. In addition, while the use of TMAs to study such questions has clear benefits, such as the rapid analysis of large number of tissue cores over identical experimental conditions and preservation of valuable patient tissue for future studies, there are also drawbacks. One is the inability of TMAs to represent the complex spatial interactions of immune inhibiting molecules in the complete tumor microenvironment. For this reason, we did not evaluate the expression of immune inhibitory molecules by TIL, as performed, for PD-L1, in the study by Calderaro et al.,+TIL count, are associated with poor HCC-specific survival in patients with resected HCC. PD-L1 and Galectin-9 expression in tumors may be induced in response to immunologic pressure which may explain why their presence is associated with prolonged survival. PD-L1 and Galectin-9 may be promising immunotherapeutic targets in HCC patients with tumors expressing these co-inhibitory molecules.In conclusion, we show that low tumor expression of PD-L1 and Galectin-9, as well as low CD8


We analyzed the inflammation by observing the monocyte chemotactic factor-1 (MCP-1) and intercellular adhesion molecule (ICAM-1) expression and calculated the tubulointerstitial fibrosis area by Masson staining. The results showed that anti-OSM antibody, rather than isotype antibody, improved EMT, inflammation, and tubulointerstitial fibrosis. In addition, the signal transducer and activator of transcription (STAT) 1 and STAT3 signaling was activated by tyrosine phosphorylation in LN mouse renal tissue, indicating that the phosphorylated STAT1 (p-STAT1) and p-STAT3 were involved in kidney injury. Moreover, decreased p-STAT3 instead of p-STAT1 has been observed after anti-OSM antibody injection. Thus, we concluded that OSM is associated with TIL in lupus nephritis, which may be connected with the activation of STAT3 rather than that of STAT1.The purpose of this study was to investigate the role of oncostatin M (OSM) in tubulointerstitial lesion (TIL) in lupus nephritis (LN). We found that OSM was highly expressed in the renal tissue of LN mice. OSM is one of the interleukin-6 cytokine family members. In order to clarify the role and mechanism of OSM in LN, mice with LN were treated with anti-OSM antibody or isotype antibody. We evaluated the tubular epithelial-mesenchymal transdifferentiation (EMT) by detecting the E-cadherin,  Systemic lupus erythematosus (SLE) is a systemic disease that can affect almost all organs in the body. During the course of the disease, there is a high incidence of kidney damage, known as lupus nephritis (LN). Kidney damage is a significant cause of death and disability in SLE patients , 2 and iβ1-induced extracellular matrix production in proximal tubule cells and could, thus, have a dual role in the regulation of cellular mechanisms associated with renal tubulointerstitial fibrogenesis [Cytokines are necessary for the occurrence and progression of LN. Oncostatin M (OSM) is a pleiotropic cytokine that belongs to the interleukin-6 cytokine family and is produced from activated T cells and monocytic cells . It has ogenesis , 11. FurIn the present study, we aimed to examine the expression of OSM in the renal tissue of LN mice and to evaluate the possible role and mechanism of OSM in TIL.MRL/MpJ and MRL/MpJ-Fas/lpr (MRL/lpr) mice were used in this study. An MRL/lpr mouse model was firstly established by Murphy and Roths by using multiple inbred mice. This model bears the lymphocyte proliferation gene (lpr) mutation, the result of a retroviral insertion in Fas gene, leading to a systemic autoimmune disease similar to human SLE, including antibody production, immunocomplex formation, and nephritis. The renal pathological changes in MRL/lpr mice are very similar with human lupus nephritis. Therefore, this kind of model is an ideal animal model to be used in the investigation of SLE. MRL/MpJ mice, as the control of MRL/lpr mice, have the same manifestation of autoimmune abnormalities. But the emergence of such symptoms is much later than that in MRL/lpr mice.Female MRL/MpJ mice were designated as the control group. And female MRL/lpr mice were randomly divided into the LN group, the anti-OSM antibody group, and the isotype antibody group. There were six mice  in each group. The mice were provided by the Model Animal Research Center of Nanjing University. All experiments with animals were approved by the Animal Care and Use Committee of Hebei Medical University. An intraperitoneal injection of anti-OSM polyclonal antibody  or isotype antibody  (R&D Systems) was administered weekly from 20 to 24 weeks of age at a dose of 1 mg/kg. All of the animals were housed in an environment with fixed light, temperature, and humidity as well as freely accessible food and water. The mice were euthanized at 24 weeks. Serum, urine, and renal cortex samples were collected for further study.After deparaffinization of the paraffin sections, Masson staining was performed to evaluate tubulointerstitial fibrosis. Collagen fibers were stained blue. The area of collagen deposition was determined as the percentage of the blue-stained area to the whole area.μg total RNA using a PrimeScript™ RT reagent Kit  following the manufacturer's recommendations. qPCR was performed with SYBR Remix Ex Taq™ II (Takara). The qPCR thermal cycling condition for all reactions was 95°C for 30 s, followed by 40 cycles of 95°C for 5 s and 55°C for 30 s. All target gene primers were purchased from Sangon Biotech . The results were expressed as relative expression levels to GAPDH gene. The CT values were used as the original data to calculate the relative expression levels of different genes by the 2−ΔΔCT method.Total RNA was isolated from the renal cortex using TRIzol reagent. Complementary DNA was synthetized from 1 The homogenate of the renal cortex was centrifuged at 1000 ×g for 10 min at 4°C, and the supernatants were collected to detect the OSM expression. The level of OSM was quantified using a competitive sandwich ELISA kit  according to the manufacturer's directions.μm sections were deparaffinized and rehydrated. Antigen recovery was performed by a microwave. Next, the sections were incubated with primary antibodies against E-cadherin and α-smooth muscle actin (α-SMA), respectively, overnight at 4°C. The antibodies were purchased from Proteintech Group . On the following day, after incubating sequentially with a biotinylated secondary antibody and horseradish peroxidase-conjugated streptavidin for 30 min at 37°C, the sections were stained with 3,3-diaminobenzidine (DAB). The negative controls were prepared by replacing the primary antibody with phosphate-buffered saline.The kidneys were dissected and fixed immediately in fixative for 24 h. The kidneys were then dehydrated, processed, and embedded in paraffin. For immunohistochemistry, 4 α-SMA, monocyte chemotactic factor-1 (MCP-1), intercellular adhesion molecule (ICAM-1), phosphorylated signal transducer, and activator of transcription 1 (p-STAT1), p-STAT3, total STAT1, total STAT3, or β-actin antibodies. The anti-β-actin antibody was purchased from ZSGB-BIO . The anti-p-STAT and total STAT antibodies were purchased from Cell Signaling . The other antibodies were purchased from Proteintech Group . Thereafter, the membranes were incubated with a horseradish peroxidase-conjugated goat anti-rabbit IgG antibody (ZSGB-BIO) and imaged using the Odyssey Infrared Imaging System .Tissue lysates were prepared as in previous studies . The proP < 0.05.The quantitative data are expressed as the mean ± standard deviation and analyzed by one-way analysis of variance (ANOVA) with the Student-Newman-Keuls test. Statistical significance was set at P < 0.05). However, MRL/lpr mice, treated with anti-OSM antibody rather than isotype antibody, had approximately 60% decrease in the level of OSM as compared to MRL/lpr mice (P < 0.05).Taking into account the dual role of OSM in renal fibrosis, we first detected the level of OSM in the renal cortex by ELISA . The datP > 0.05), but the amount of BUN and Upro in MRL/lpr mice was significantly increased . And treatment with anti-OSM antibody decreased the amount of BUN and Upro . However, there was no change in the level of BUN and Upro after isotype antibody injection (P > 0.05).Serum creatinine (SCr), blood urea nitrogen (BUN), and 24-hour urinary protein (Upro) were detected . There wP > 0.05). The administration of anti-OSM antibody suppressed the expression level of p-STAT3 by 41.21% (P < 0.05) but only induced a small, not statistically significant decrease in the expression of p-STAT1 (P > 0.05). However, total STAT1 and STAT3 expression were not affected by this treatment (P > 0.05).STAT signaling is one of the main signals activated by OSM. In order to clarify whether STAT1 and STAT3 are involved in OSM-mediated kidney injury, we examined the effect of anti-OSM antibody on the activation and expression of STAT1 and STAT3 in the kidneys of MRL/lpr mice. As shown in α-SMA, and fibroblast-specific protein 1. In this study. we examined the expression of E-cadherin and α-SMA in the renal cortex. The results by immunohistochemistry staining  and a depressed expression of α-SMA   is an important event in tubulointerstitial fibrosis. EMT is characterized by the downregulation of epithelial marker proteins such as E-cadherin, cytokeratin, and zonula occludens 1 and upregulation of mesenchymal markers including vimentin, staining  showed t Figures . The exp protein .P < 0.05). Anti-OSM antibody treatment inhibited the protein expression of MCP-1 by 44.91% and ICAM-1 by 32.03% (P < 0.05). Moreover, we observed the effect of anti-OSM antibody on the expression of MCP-1 and ICAM-1 mRNA and found that in MRL/lpr mice, the mRNA level of MCP-1 and ICAM-1 also increased . However, anti-OSM antibody administration ameliorated this response (P < 0.05)  .P < 0.05) in aniline blue-positive areas (blue area) was observed in the renal interstitium in MRL/lpr mice, and the administration of anti-OSM antibody reduced such areas by 69.08% (P < 0.05)  .α-SMA, suppressed the expression of MCP-1 and ICAM-1, attenuated renal fibrosis, and partially improved 24-hour urinary protein excretion and BUN production. In addition, the effects of OSM in the TIL of LN mice may be connected with the activation of STAT3 instead of STAT1 signaling.Using anti-OSM antibody, we provided evidence that OSM participates in the TIL of lupus nephropathy. We have shown that anti-OSM antibody increased the expression of E-cadherin and decreased the expression of We previously found that OSM induced EMT and extracellular matrix secretion of tubular epithelial cells in vitro via the activation of the Janus kinase (JAK)/STAT pathway . It suggWe then explored the mechanism of OSM in TILs. The JAK/STAT signaling pathway is one of the pivotal signals activated by OSM. The STAT protein family comprises six members, STAT1 through STAT6. Both STAT1 and STAT3 can be activated by OSM . Earlierβ1. Therefore, they suggested that depending on the cellular microenvironment and/or the specific injury, OSM may indeed have the ability to act as an anti- or profibrotic molecule [However, Sarkozi found that besides the OSM-mediated induction of morphological alterations indicative of renal tubular EMT, it can act as an inhibitor of the profibrotic effector cytokine TGF-molecule . Considemolecule , 17. Formolecule , 19. Mormolecule  showed tThrough this study, we concluded that OSM is associated with TIL in lupus nephritis, which may be connected with the activation of STAT3 rather than that of STAT1.


Acinetobacter baumannii, a major hospital-acquired pathogen, is a serious health threat and poses a great challenge to healthcare providers. Although there have been many genomic studies on the evolution and antibiotic resistance of this species, there have been very limited transcriptome studies on its responses to antibiotics. We conducted a comparative transcriptomic study on 12 strains with different growth rates and antibiotic resistance profiles, including 3 fast-growing pan-drug-resistant strains, under separate treatment with 3 antibiotics, namely amikacin, imipenem, and meropenem. We performed deep sequencing using a strand-specific RNA-sequencing protocol, and used de novo transcriptome assembly to analyze gene expression in the form of polycistronic transcripts. Our results indicated that genes associated with transposable elements generally showed higher levels of expression under antibiotic-treated conditions, and many of these transposon-associated genes have previously been linked to drug resistance. Using co-expressed transposon genes as markers, we further identified and experimentally validated two novel genes of which overexpression conferred significant increases in amikacin resistance. To the best of our knowledge, this study represents the first comparative transcriptomic analysis of multidrug-resistant A. baumannii under different antibiotic treatments, and revealed a new relationship between transposons and antibiotic resistance.Multidrug-resistant  Acinetobacter baumannii is a nosocomial pathogen that can grow in diverse environments, including intensive care units. Immunocompromised patients are vulnerable to A. baumannii infection even during therapy. These bacteria enter the body through moist tissues and can colonize various sites, such as the respiratory tract, central nervous system, skin, and eyes. Pneumonia, blood stream infections, and meningitis are the most frequent adverse effects of infection1. The major challenge in the treatment of A. baumannii infection is multidrug resistance. Pan-drug-resistant A. baumannii strains have been reported across Asia and Europe4.A. baumannii have discussed the relationships among the variability of drug resistance islands and drug-resistant phenotypes4. Multidrug-resistant strains possess a higher metabolic capacity in environments with limited resources5. Nonetheless, information from genome sequences is not sufficient to capture the dynamics of gene expression. Several transcriptome studies have probed the transcriptional changes in the A. baumannii reference strain ATCC17978 when grown under harsh environmental conditions, such as ethanol treatment6, high salinity7, and iron deficiency8. These studies particularly noted the strong survivability of A. baumannii under such conditions. Recent transcriptome studies have also investigated the response of this species to antibiotics. For example, a study in which the A. baumannii reference strain ATCC19606 was treated with colistin and doripenem revealed the critical genes involved in the killing process of colistin9, while in another study the multidrug-resistant A. baumannii strain MDR-ZJ was treated with tigecycline and identified an efflux pump and several transcriptional regulators involved in the drug resistance response10. These studies were performed using only single strains, which may limit the generalizability of their conclusions. Due to the large variations in genome sizes and sequences among different strains, especially between multidrug-resistant and -sensitive ones, a more systematic analysis that is free from strain bias is needed to study and compare their transcriptomes under antibiotic-free and -treated environments.Several comparative genomic studies of A. baumannii, we conducted a comparative study of nine multidrug-resistant strains, five of which are pan-drug-resistant, and three sensitive strains using a strand-specific RNA-sequencing protocol. We adopted a de novo transcriptome assembly and analysis pipeline to study gene expression in the form of polycistronic transcripts. Differentially expressed genes were analyzed according to the corresponding strain properties. Three multidrug-resistant strains were further treated with three antibiotics, namely amikacin, imipenem and meropenem, and the corresponding transcriptomes were generated and analyzed. Our results indicated that genes associated with transposable elements in general were up-regulated under antibiotic treatment. Many of these genes are known to be drug resistance-related. Among several previously unknown transposon-associated genes, we experimentally validated two of them. Expression of these two genes in E. coli BL21 conferred increased resistance to amikacin. In summary, we believe our comparative transcriptomic study and polycistronic transcript analysis revealed new insights into the drug resistance response in A. baumannii. Our analytical approach should also be applicable to similar studies of other bacterial pathogens.Herein, to better understand the transcriptomic response of drug resistance in 4 of multidrug-resistant A. baumannii .Twelve strains with different pulsed-field gel electrophoresis (PFGE) patterns Fig. S and antinii Fig. . The othnii Fig.  based on11 across 29 samples. 38.8% of the assembled transcripts could be annotated based on known genes from 15 complete A. baumannii genomes on the transcribing strand, while the other 61.2% of the transcripts could be classified into ERCC spike-in sequences, antisense transcripts, or mis-assembled transcripts. Among these annotated transcripts, over 75% were polycistronic, along which more than one gene could be annotated   , imipenem, and meropenem (both of the carbapenem class) were chosen, because the 12 strains had exhibited various degrees of resistance to these three antibiotics. In total, 18 antibiotic-treated samples were prepared from either mid-log or stationary phases, but only 17 samples, excluding the amikacin-treated R4 at mid-log phase, were successfully sequenced. RNA sequencing generated a read depth of over 1,000× per sample. A total of 177,939 transcripts were assembled by Trinitypt Fig. S. Genes t1) Fig. S. Many of1) Fig. S.q < 0.01) followed by the Benjamini–Hochberg procedure . A total of 559 genes were up-regulated and 910 genes were down-regulated in treatment with at least one of the three antibiotics Fig. S. Among tA. baumannii strains exhibited distinct responses to the two classes of antibiotics , including two protein-folding chaperons (DnaK and HtpX), several peptidyl-prolyl isomerases, and the CLP protease system .To investigate the driving factors, other than the expression of antibiotic resistance genes, of drug resistance, we also examined the extent to which antibiotic resistance genes appeared in polycistronic transcripts. Known antibiotic resistance genes were annotated in over 67% of the polycistronic transcripts Fig. . Over 50q < 0.01) followed by the Benjamini–Hochberg procedure  . These findings led to the observation that up-regulated drug resistance genes were preferentially those coding for drug inactivation enzymes (p = 0.007)  based on the two-tailed Student’s t-test. They also showed greater up-regulation fold changes than non-transposon-associated antibiotic resistance genes, with significant p-values in Wilcoxon’s rank-sum test (p < 0.05)  to be analyzed. The expression distributions of transposon-associated genes did not show significant differences from non-transposon-associated genes at the mid-log phase under antibiotic-free conditions Fig. . However01) Fig. . This ob01) Fig. . Transpo7) Fig. S. It was 7) Fig. S. Further05) Fig. . However18. In addition, we identified that two transposon-associated genes, namely, mph, which codes for the macrolide 2′-phosphotransferase homolog, and mel, which codes for the macrolide efflux protein homolog, were assembled onto the same transcript downstream of the transposon gene tnpD in all amikacin-resistant strains , and were also identified in the genomes of A. baumannii strains MDR-TJ and TYTH-1  confirmed that bed Fig. , while ted Fig. S. It is nels Fig. . To stud21 Table . Their p21 Table . Both meons Fig. . The MICA. baumannii strains, cultured them with or without antibiotic treatment, and developed a de novo assembly-based method, by which polycistronic transcripts, the major form of transcription in bacteria, could be reconstructed, to analyze the comparative transcriptomics. This novel method of analysis revealed, for the first time, that the regulation of antibiotic resistance genes was performed at the level of operons. Antibiotic resistance genes were systematically analyzed to determine, first, with which genes they were co-transcribed, and second, which genes and pathways were significantly modulated under treatment with antibiotics.Comparative genomics studies have been widely conducted to understand the evolution of pathogens toward multidrug resistance. However, knowledge of the global regulation of antibiotic resistance genes is still inadequate, due to the lack of RNA-seq data and suitable methodologies for comparative transcriptomics. In this study, we collected nine multidrug-resistant and three multidrug-sensitive A. baumannii. Many genes involved in these pathways were also reported to be up-regulated in Wolbachia under doxycycline treatment22. Moreover, the strains also responded differently to the two classes of antibiotics. Amikacin, an aminoglycoside that targets the translation machinery, induced up-regulation of over 149 genes, among which were genes involved in protein folding and lysis, while only 4 genes were down-regulated. In contrast, the two carbapenem-related antibiotics (imipenem and meropenem) led to a general down-regulation of gene expression, including of a large number of transcription factors. In addition, most of the imipenem- and meropenem-specific genes encoded either hypothetical proteins or proteins without functional annotation. Thus, there remains a large knowledge gap concerning our understanding of the transcriptional response under carbapenem treatment.First, our data suggested that under treatment with both classes of antibiotics, genes in several operons that are involved in ATP, RNA, and protein synthesis were simultaneously up-regulated, suggesting that the rates of energy and protein production were generally elevated among multidrug-resistant A. baumannii. A wide spectrum of antibiotic resistance genes have been identified in all strains, including the resistant and sensitive ones , H-NS (G3933) and IFH (G4261)  Table . It woulet al.29. The PFGE patterns were clustered using the Unweighted Pair Group Method with Arithmetic Mean. Different lineages were determined by a similarity cutoff of 80%, with 1.5% position tolerance and 1% band optimization. The minimum inhibitory concentrations (MICs) of the antibiotics were determined according to Wiegand et al.30. Multilocus sequence typing was performed as described at PubMLST (http://pubmlst.org/abaumannii/). Strains with different lineages or antibiotic resistance properties were selected for further study.All strains were isolated from patients at hospitals in Hong Kong Tables  and S2. 31. Briefly, the bacteria were grown in 5% blood agar overnight. Bacterial suspension were prepared to a turbidity equivalent to 0.5 McFarland. Bacteria were inoculated to the antibiotic-containing Mueller-Hinton agar plates and incubated at 37 °C for 16 hours and the MICs were read.The MIC of the strains was determined and interpreted according to the criteria of Clinical and Laboratory Standards Institute (CLSI)A. baumannii was first cultured in BHI broth overnight. 1 ml overnight culture was inoculated to 100 ml fresh BHI broth. The mid-log (OD600 ~ 1.00) and stationary (OD600 ~ 2.1) samples were harvested. The bacteria cultures were incubated at 37 °C with 200 rpm shaking.To determine the optimal antibiotic concentrations for the antibiotic-treated conditions in LB, 2-fold serial dilutions were performed, starting with the MICs as previously determined, to discover the maximum antibiotic concentrations at which bacterial growth was not significantly inhibited compared with that in an antibiotic-free medium. The final antibiotic concentrations used, in a range from 1/8 to 1/64 of the MICs, are listed in Table g for 10 minutes at room temperature. Two to 4 ml of RNAprotect (Qiagen) was added to the pellet and mixed by vortexing. The pellet was re-precipitated by centrifugation at 3,500 g for 10 minutes at room temperature, and the supernatant was discarded. Standard TRIzol (Life Technologies) protocol was then applied to extract total RNAs from the cell pellets. To ensure that the DNA was completely removed, DNase digestion was performed and the total RNA samples were further purified by acidic phenol–chloroform. mirVana (Life Technologies) was used to deplete tRNAs and other small RNA portions, and the large RNA molecules were retained. Ribosomal RNAs were then removed by Ribo-Zero rRNA removal kits for gram-negative bacteria (Epicentre). External RNA Controls Consortium (ERCC) RNA Spike-in Control Mixes (Ambion) were added to each rRNA-depleted RNA sample according to the user guide. The sequencing libraries were prepared using a ScriptSeq v2 RNA-seq Library Preparation kit (Epicentre) with rRNA-depleted samples, and all of the libraries were sequenced by Illumina HiSeq 2000 following the strand-specific sequencing protocol for 100 cycles. All RNA-seq data have been deposited to SRA with the accession SRP075337.Ten to 15 ml of bacteria culture was pelleted by centrifugation at 3,500 32 with the following parameters: SLIDINGWINDOW:4:20 and MINLEN:50.The first six bases of reads and the adaptors were first removed by in-house-developed pipelines. Then, low-quality sequences were trimmed by Trimmomatic 0.3011 with default parameters and specifying–SS_lib_type as FR. All transcripts were annotated using BLAST based on the 15 full A. baumannii genomes retrieved from the NCBI  were determined by a spatial angular method (refer to the Supplementary methods for a detailed description). Differentially expressed genes between antibiotic-free conditions and antibiotic-treated conditions were determined by the following set of criteria: (1) to be considered as an up-regulation under antibiotic treatment, the normalized expression value of the gene in the treated sample at mid-log phase must be larger than or equal to 50 RPKM; and to be considered as a down-regulation, the normalized expression value of the gene in the untreated sample at mid-log phase must be larger than or equal to 50 RPKM; (2) for up-regulation under antibiotic treatment, the normalized expression value of the gene in the treated sample at mid-log phase must be at least 2-fold larger than that in the untreated sample; for down-regulation under antibiotic treatment, the normalized expression value of the gene in the untreated sample at mid-log phase must be at least 2-fold larger than that in the treated sample; (3) finally, for up-regulation under antibiotic treatment, according to (2), the normalized expression value of the gene in the treated sample at stationary phase must be larger than that in the untreated sample at mid-log phase; and for down-regulation, according to (2), the normalized expression value of the gene in the untreated sample at mid-log phase must be larger than that that in the treated sample at stationary phase. Any gene that was up-regulated in at least two out of three strains and at the same time did not show any down-regulation was considered a common up-regulated gene (and conversely for the common down-regulated genes). However, because the amikacin-treated R4 sample at mid-log phase had failed to be sequenced, only genes up-regulated or down-regulated in both the R3 and R5 strains were used to determine common differentially expressed genes for amikacin. For Fig. A. baumannii genomes were selected, whereas transposon-related genes and common drug resistance genes were excluded. The sequences were aligned separately using MUSCLE35 3.8.31 and only the aligned regions were then extracted and concatenated. The phylogenetic trees were constructed using the neighbor-joining method in MEGA 636. To annotate GO terms to each gene, BLASTX searches for all of the genes were performed against the nr protein database with default parameters, and only the top 50 hits were retained, which were then annotated by Blast2GO37 with default parameters. GO enrichment was measured in terms of q-values, calculated based on a hypergeometric distribution and the Benjamini–Hochberg procedure. The q-values of the functional correlation of the GOs were determined using a chi-square distribution in a contingency table and with the Benjamini–Hochberg procedure.Details of the expression normalization are described in the supporting documents, under headings Angular based linear regression, Finding the best regression model and Normalizing samples in different conditions. For phylogenetic analysis, genes that were expressed in the antibiotic-free samples of all strains and could be identified in all 15 of the complete Power SYBR Green PCR master mix (Life Technologies) was used according to the standard protocol. A master mix solution was made for each sample. Each 20 μl technical replicate contained 5 ng templates, 375 nM primers Table , and 1× E. coli RNase H was added to the mixture and incubated at 37 °C for 20 minutes.The SuperScript III first-strand synthesis SuperMix for qRT-PCR (Life Technologies) was used. The reaction mixture was prepared according to the standard protocol. The mixture was first incubated at 25 °C for 10 minutes, followed by incubation at 50 °C for 30 minutes. The reaction was terminated at 85 °C for 5 minutes and cooled over ice. 2 U of A 50-μl reaction mixture was prepared for each PCR reaction, including 45 μl Platinum PCR SuperMix (Life Technologies) solution, 5 μM primers Table  and 5 ngAll plasmids were constructed either using a Champion™ pET101 Directional TOPO® Expression Kit following the standard protocol, or by a gene synthesis service from GenScript  on pET15b, which is the closest plasmid to pET101 in the sequence Table . 1 to 10Bacterial cells were harvested after 4 hours induction in 1 mM IPTG. The OD600 values were adjusted to 1.0. All samples were lyzed in bacterial lysis buffer (1% SDS in PBS) and loaded onto 12% SDS-PAGE for western blot analysis. 1:3000 anti-HIS antibodies (GE 27-4710-01) and 1:2000 anti-FLAG antibodies (Sigma F3165) in 5% fat-free milk were used as primary antibodies to detect the expression of the candidate resistance genes, engineered with either an HIS-tag (for AacBI and Mel) or a FLAG-tag (for Mph).600 was equal to 0.4. 1 mM IPTG was added and the bacteria were incubated for 4 hours to induce protein expression. The culture was diluted to a final OD600 of 0.01. Amikacin at the desired concentrations along with 1 mM IPTG were added, and the bacteria were incubated at 37 °C and 150 rpm. The OD600 values were taken every one hour.Bacteria transformed with the expression vector were incubated at 37 °C in LB at 150 rpm until ODSupplementary methodsSupplementary figuresSupplementary tables 1–7Supplementary table 8


Background: Previous research exploring the psychometric properties of the scores of measures of posttraumatic stress disorder (PTSD) suggests there is variation in their functioning depending on the target population. To date, there has been little study of these properties within UK veteran populations.Objective: This study aimed to determine optimally efficient cut-off values for the Impact of Event Scale-Revised (IES-R) and the PTSD Checklist for DSM-5 (PCL-5) that can be used to assess for differential diagnosis of presumptive PTSD.Methods: Data from a sample of 242 UK veterans assessed for mental health difficulties were analysed. The criterion-related validity of the PCL-5 and IES-R were evaluated against the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5). Kappa statistics were used to assess the level of agreement between the DSM-IV and DSM-5 classification systems.Results: The optimal cut-off scores observed within this sample were 34 or above on the PCL-5 and 46 or above on the IES-R. The PCL-5 cut-off is similar to the previously reported values, but the IES-R cut-off identified in this study is higher than has previously been recommended. Overall, a moderate level of agreement was found between participants screened positive using the DSM-IV and DSM-5 classification systems of PTSD.Conclusions: Our findings suggest that the PCL-5 and IES-R can be used as brief measures within veteran populations presenting at secondary care to assess for PTSD. The use of a higher cut-off for the IES-R may be helpful for differentiating between veterans who present with PTSD and those who may have some sy`mptoms of PTSD but are sub-threshold for meeting a diagnosis. Further, the use of more accurate optimal cut-offs may aid clinicians to better monitor changes in PTSD symptoms during and after treatment. These measures often utilize cut-off scores to indicate presumptive PTSD. An examination of the literature suggests that there is much variation in the recommended cut-offs. For example, Keen et al.  is the most widely used and accepted criterion measure of PTSD  within a sample of treatment-seeking UK veterans recruited from a secondary care setting. The study aimed to identify cut-off values for making a differential diagnosis of PTSD. This was done by collecting data during clinical assessments that were conducted at a national charity in the UK which supports veterans with mental health difficulties.3.3.1.Data was collected from a national charity in the UK called Combat Stress (CS) that offers clinical services to veterans with mental health difficulties. As part of the referral process to CS, individuals were triaged by a nurse and then those identified as experiencing mental health difficulties, using a standardized clinical interview, were offered a formal assessment to screen for presence of PTSD and other mental health difficulties. These assessments were conducted by certified Clinical Psychologists and CBT therapists. Therapists had all been trained by the same psychiatrist on how to administer the CAPS-5 and further supervision was provided aimed at improving fidelity. During this assessment a standard set of psychometric measures were administered. The PTSD Checklist for DSM-5 (PCL-5) and Impact of Event Scale-Revised (IES-R) were counter-balanced with approximately half the packs of measures having the PCL-5 at the start and the IES-R at the end and vice versa. Data was collected over a six-month period from February 2016 to July 2016 from 223 participants. In addition, we included data from 23 individuals who had already been assessed in the three months prior to February 2016, had completed the standardized batch of psychometric measures and subsequently been screened negative for PTSD on the PCL-5. The rationale for this was to ensure there was sufficient variation in PTSD caseness and severities to be able to conduct statistical analysis . The assessor then administered the CAPS-5. Whilst the IES-R does not directly overlap with the DSM-IV PTSD, it assesses for three clusters of symptoms that map onto the three main DSM-IV symptom criterions B, C and D for PTSD. The other two measures assessed the DSM-5 PTSD symptoms. Socio-demographic characteristics were also collected. These included sex, age, educational achievement and current employment status.3.3.1.The CAPS-5 is a structured clinical interview that includes 30 items  scored 0–4. Total scores can range from 0 to 80. Initial work has suggested a cut-off of either 33 or 38 for veterans being screened for symptoms of PTSD . For the remaining participants, no missing data was present for individual items from these measures. Following Kraemer’s  were excluded from the analysis (raemer’s  guidelinraemer’s . Kraemerraemer’s  recommenThe area under the ROC curve (AUC) and its associated 95% confidence intervals were calculated for each test using the DeLong method. The AUC value can vary between 0.5 and 1 and represents the overall accuracy of the diagnostic test in predicting diagnostic caseness  curves were fitted using the pROC package  of the 242 participants met the DSM-5 diagnostic criteria for PTSD according to CAPS-5.Of the 246 participants, four did not complete the IES-R and were excluded from the analysis, leaving an effective sample of 242 participants who had no missing data. Data presented in ĸ(0.5) = 0.52 (95% CI: 0.39–0.65), suggesting moderate agreement with CAPS-5. The associated uncalibrated sensitivity was 0.89 (95% CI: 0.85–0.94) and the uncalibrated specificity was 0.63 (95% CI: 0.50–0.76). The quality of sensitivity [ĸ(1)] and specificity [ĸ(0)] were both 0.52. The values corresponding to other tests of performance, including the positive predictive value, negative predictive value and efficiency, are presented in Supplemental data n = 188) of the 242 participants would screen positive for PTSD  = 0.63; Negative Predictive Value (NPV) = 0.63).Following Kraemer’s  guidelinĸ(0.5) = .51 (95% CI: 0.39–0.63), indicating moderate agreement with CAPS-5. The associated uncalibrated sensitivity was 0.83 (95% CI: 0.78–0.88) and the uncalibrated specificity was 0.74 (95% CI: 0.62–0.86). The quality of sensitivity [ĸ(1)] for this cut-off value was 0.43 and the quality of specificity [ĸ(0)] was 0.63. Supplemental data n = 170) of the 242 participants would screen positive for PTSD .The QROC analysis of the IES-R revealed an optimally efficient cut-off score of 46. The associated quality of efficiency index value was Z = −0.21, p = .834). Both ROC curves are depicted in p < .001) between the previously recommended PCL-5 cut-off score of 33 and the IES-R cut-off score of 33. This represents observed agreement of 84.3% versus the expected agreement of 68.6% . Observed agreement was 83.1% and expected agreement was 64.0%. With the optimal cut-offs identified within this paper (i.e. 34 for PCL-5 and 46 for IES-R), the kappa value was 0.53 , indicating moderate agreement. This represents observed agreement of 81.8% relative to the expected agreement of 61.2%  using the PCL-M to define caseness against both the DSM-IV and DSM-5 (Roth, St Cyr, Levine, King, & Richardson, Due to a gap in the literature, the aim of the current study was to explore the utility of various brief PTSD screening measures within clinical populations of UK veterans. As such, the sample recruited should increase the ecological validity of our findings and improve generalizability. That said, there are a number of limitations that need to be considered when interpreting the results of the current study. Firstly, whilst the sample employed is appropriate to explore the utility of the PCL-5 and IES-R within treatment-seeking veterans, its lack of diversity may limit the generalizability of the findings to other populations, or possibly to epidemiological surveys of community veteran populations. Indeed, a previous review of the PTSD Checklist for DSM-IV suggested that cut-offs to indicate PTSD need to take into account both the population and function of the psychometric measure (Keen et al., Whilst the aim of this paper was to explore optimal cut-offs for the PCL-5 and IES-R for UK veterans, it is worth noting that there could be limitations to dichotomizing health outcomes. Harrell has written about a number of limitations that may result from dichotomizing continuous variables Harrell, . For exa5.1.The data presented supports the use of these brief psychometric measures to assess for the presence of PTSD within clinical samples of UK veterans. In particular, the specificity and sensitivity scores for PCL-5 and IES-R suggest these are favourable measures that can be administered to veterans directly for them to complete themselves. Our data indicates the importance of using cut-offs that are appropriate to the target population. Appropriate cut-off scores for the PCL-5 and IES-R were found to be optimal at 34 and 46 respectively. For UK veterans seeking mental health support, the use of higher cut-off values appeared to improve the function of the tests.Click here for additional data file.


Validation study using data from a multicenter, randomized, clinical trial (RCT).Quick Disabilities of the Arm, Shoulder, and Hand (Quick-DASH) in patients with a simple elbow dislocation.To evaluate the reliability, validity, responsiveness, and minimal important change (MIC) of the Dutch version of the Oxford Elbow Score (OES) and the Quick-DASH in these patients are not fully known.Patient-reported outcome measures are increasingly important for assessing outcome following elbow injuries, both in daily practice and in clinical research. However measurement properties of the OES and Quick-DASH were completed four times until one year after trauma. Mayo Elbow Performance Index, pain (VAS), Short Form-36, and EuroQol-5D were completed for comparison. Data of a multicenter RCT (n = 100) were used. Internal consistency was determined using Cronbach’s alpha. Construct and longitudinal validity were assessed by determining hypothesized strength of correlation between scores or changes in scores, respectively, of (sub)scales. Finally, floor and ceiling effects, MIC, and smallest detectable change (SDC) were determined.OES and Quick-DASH demonstrated adequate internal consistency . Construct validity and longitudinal validity of both scales were supported by >75% correctly hypothesized correlations. MIC and SDC were 8.2 and 12.0 point for OES, respectively. For Quick-DASH, these values were 11.7 and 25.0, respectively.OES and Quick-DASH are reliable, valid, and responsive instruments for evaluating elbow-related quality of life. The anchor-based MIC was 8.2 points for OES and 11.7 for Quick-DASH.OES and  Musculoskeletal elbow injuries may influence health and quality of life –3. PhysiThe best elbow-specific questionnaire currently is the Oxford Elbow Score (OES). This originally English patient-reported questionnaire measures injury-related quality of life in patients following surgery of the elbow joint –10. The Quick-DASH is a shortened version of the DASH [The most often used questionnaire for upper extremity injuries is the Disability of the Arm, Shoulder, and Hand (DASH). It was designed to describe disability experienced by patients with any musculoskeletal condition of the upper extremity and to monitor change in symptoms and upper limb function over time . The DASthe DASH .Quick-DASH in patients with a simple elbow injury are not fully known. The Minimal Important Change (MIC), which is an important input parameter for sample size calculations in clinical studies, is not available for these scores.Measurement properties of the OES and Quick-DASH in adult patients with a non-operatively treated simple elbow dislocation. The Mayo Elbow Performance Index, two general health-related quality of life instruments and subscales , and pain measured with a Visual Analog Scale were used for comparison.The aim of the current study was to evaluate the reliability, validity, responsiveness, and minimal important change of the OES and the Data of a multicenter randomized clinical trial comparing early functional treatment with plaster immobilization in patients after a simple elbow dislocation  were used. The trial is registered at the Netherlands Trial Register (NTR2025). The results of this study and the study protocol are published elsewhere , 22. Thei.e., stiff or painful elbow or neurological disorder); 6) previous operations or fractures involving the elbow; and 7) expected problems with completing follow-up . Baseline characteristics were gender, age, affected side, and hand dominance. Patients completed a set of questionnaires during outpatient visits at six weeks and at three, six, and 12 months after randomization.Patients were recruited from August 25, 2009 until September 18, 2012. Inclusion criteria were 1) age of 18 years or older; 2) a simple elbow dislocation with successful close reduction; and 3) written informed consent. Exclusion criteria were 1) polytraumatized patients; 2) recurrent or open dislocation; 3) additional traumatic injuries of the affected arm; 4) surgical intervention; 5) impaired elbow function prior to trauma (http://www.isis-innovation.com/).The OES is a 12-item, three domain  questionnaire, reflecting injury-related quality of life. Each domain is transformed into a 100-point metric scale with higher score representing better outcome . The samQuick-DASH contains 11 items (scored 1–5) and reflects both function and pain in persons with musculoskeletal disorders of the upper extremity. To be able to calculate a score, at least 10 of the 11 items must be completed. The score is calculated using the formula: -1)*11). The overall score ranges from 0 to 100 points with higher score representing greater disability [Quick-DASH compared with the DASH [The DASH is the most used questionnaire for disorders across the entire upper extremity. Validated versions are available in a multitude of languages, including Dutch. Sufficient validity, reliability, and responsiveness of the DASH has been shown for disorders across the entire upper extremity . The Quisability , 25. Relthe DASH .The Mayo Elbow Performance Index (MEPI) consists of four domains: pain , range of motion (20 points), stability , and function . Each domain is transformed into a 100-point scale with higher score representing better outcome .A Visual Analog Scale (VAS) was used to measure the level of pain. The ends of the 100-mm horizontal line showed the word descriptors ‘no pain’ at 0 mm and ‘worst pain imaginable’ at 100 mm) .The SF-36 is a validated 36-item health survey. It represent eight health domains , role limitations due to physical health , bodily pain , and general health perceptions , vitality, energy, or fatigue , social functioning , role limitations due to emotional problems , and general mental health  that are combined into a physical and a mental component summary . The score ranges from 0–100 with higher scores representing higher quality of life. The scores are converted and compared with the norms for the general population of the United States . A validThe EQ-5D-3L is a validated instrument for measuring health-related quality of life. The EQ-5D utility score (EQ-US) ranges from 0 to 1 and is determined from five 1-item domains: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. In addition, the individual’s rating of his/her quality of life state is recorded by means of a standard Visual Analog Scale (EQ-VAS), which ranges from 0 to 100. Higher scores represent better health-related quality of life , 31. A vQuick-DASH (sub)scales were determined by comparing these (sub)scales with the VAS (for pain) MEPI, SF-36, and EQ-5D.Analyses were performed using the Statistical Package for the Social Sciences (SPSS) version 21. The receiver operating characteristic (ROC) curve and Youden index were analyzed using MedCalc 14.10.2 software . Data are reported in compliance with the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guidelines. Since raw data for individual items were analyzed, missing data were not imputed. Descriptive statistics was used in order to describe the main characteristics of the study participants. Measurement properties of the OES and Internal consistency is a measure of the extent to which items in a (sub)scale are correlated (homogeneous), thus measuring the same concept . For eacQuick-DASH, MEPI, SF-36, and EQ-5D. Similar procedures were followed for the Quick-DASH. Since all data deviated from a Normal distribution scale), Spearman’s Rho (rank correlation) coefficients (r) were determined. Strengths of correlation was categorized as high (r>0.6), moderate (0.3<r<0.6), or low (r<0.3) [Validity is the degree to which a questionnaire measures the construct it is supposed to measure. As there was no gold standard in the current study, the validity of the OES was expressed in terms of the construct validity. Construct validity represents the extent to which scores on a specific questionnaire relate to other measures in a way that is in agreement with prior theoretically derived hypotheses concerning the concepts that are being measured . The six (r<0.3) . Constru (r<0.3) . PredefiQuick-DASH (sub)scales and changes in all other (sub)scales. Change scores were calculated as the difference in score at six weeks  and the final score at 12 months follow-up. Since all change scores deviated from a Normal deviation, Spearman correlation coefficients were calculated. Predefined hypotheses are shown in Responsiveness refers to the ability of a questionnaire to detect clinically important changes over time . Longitui.e., score at 12 months–score at six weeks) by the standard deviation of the first measurement [i.e., score at 12 months–score at six weeks) divided by the standard deviation of this change [The effect size (ES) and standardized response mean (SRM) were determined as measures of the magnitude over time. The ES was calculated by dividing the mean change in score between two time points (surement . The SRMs change . These es change . Large eFloor and ceiling effects are present if more than 15% of the study population rates the lowest (floor effect) or highest (ceiling effect) possible score on any questionnaire (sub)scale . In the The minimal important change (MIC) is defined as the smallest measurable change in outcome score that is perceived as significant by patients . An anchi.e., the associated criterion of the Youden index) reflects the MIC. This MIC is shown with its 95% confidence interval (CI) after bootstrapping (1000 replicates and 900 random-number seeds).As an alternative, MIC was also calculated for the total scores by plotting the receiver operating characteristic (ROC) curve of the change in score for patients who scored ‘slightly better’ on the transition item versus patients who scored ‘no change’. The optimal ROC cutoff point (change) by the square root of two [change / square root of 2) [In addition to the MIC, the Smallest Detectable Change (SDC) was determined. SDC is defined as the smallest intra-personal change in score that represents (with p<0.05) a ‘real’ difference above measurement error . As patit of two . SEM cant of two . For theot of 2) . Ideallyot of 2) .25-P75 32–59) and 42 patients were male. The dislocation involved the right arm in 53 patients, and the dominant side was affected in 46 patients. One patient was lost to follow-up and six missed one follow-up visit.One hundred patients were included, of which 48 were treated with early mobilization and 52 with plaster immobilization for three weeks. The median age was 46 year scales scales . InternaQuick-DASH and MEPI, 9 out of 12 correlations (75%) were as hypothesized, also showing sufficient construct validity.Construct validity is shown in Quick-DASH, indicating sufficient longitudinal validity for both instruments. Longitudinal validity was also sufficient for the OES subscales, with 83% (10/12), 75% (9/12), and 100% (12/12) hypotheses predicted correctly for the OES pain, function, and social-psychological subscale, respectively.Longitudinal validity is shown in Quick-DASH instruments is shown in Quick-DASH, the SRM was large (0.87), but the ES was only moderate (0.73).The standardized response mean (SRM) and the Effect Size (ES) of the OES and Quick-DASH (29%), and SF-36 BP (30%) demonstrated a ceiling effect. The OES as a total scale demonstrated a ceiling effect only from six months onwards, where 26% of the patients reported the maximum score.None of the instruments evaluated showed a floor effect. From six weeks onwards the OES function, MEPI, VAS, SF-36 PF, and EQ-5D US demonstrated a ceiling effect ; 20%, 32i.e. r > 0.29) with the change scores of the OES total scale, the OES pain and function subscales, and the Quick-DASH. Spearman’s rank correlations with the transition item were below this threshold for the OES psychosocial subscale (r = -0.20) and all other (sub)scales. Therefore the MIC for the these could not be determined reliably.The number of patients per transition item for the different time intervals is shown in Quick-DASH change score was 3.5 (95% CI 1.6–5.5) points. The ROC curve analysis produced similar results, with wider confidence intervals. There the MIC was 6.3 (95% CI 4.2–8.3) points for the OES and 4.5 (95% CI 2.3–11.4) for the Quick-DASH.For the OES, the anchor-based MIC was 8.2 points (95% CI 5.7–10.7) for the total scale, 7.3 (95% CI 3.3–11.4) points for the pain subscale, 5.6 (95% CI 2.0–9.2) points for the function subscale, and 11.7 (95% CI 7.6–15.9) points for the social-psychological subscale . The ancQuick-DASH.For each of these four (sub)scales, the MIC was smaller than the SDC values. These SDC was 12.0 (SEM 4.3) for the OES total scale, 12.9 (SEM 4.6) for the OES pain subscale, 14.1 (SEM 5.1) for the OES function subscale, 25.0 (SEM 9.0) for the OES social-physiologic subscale, and 12.2 (SEM 4.4) for the Quick-DASH are reliable, valid, and responsive instruments for the evaluation and follow-up of patients after a simple elbow dislocation that was treated non-operatively. The anchor-based MIC was 8.2 points for OES and 3.5 for Quick-DASH.This study showed that the OES and Quick-DASH  was comparable with published values [The reliability of the OES  and d values , 40–44. d values .Quick-DASH and SF-36 BP and PCS. The latter is a novel observation, as no data were available on the correlation between the OES and SF-36 subscales. Correlation with the Quick-DASH and MEPI has been published before for patients who had undergone elbow surgery [The OES proved its validity by demonstrating strong correlations with the  surgery , 15.Quick-DASH in non-operatively treated patients with an elbow dislocation. Construct validity of the (Quick-)DASH has been reported before [Quick-DASH are comparable with data from Dawson et al. [Quick-DASH and MEPI. The moderate correlation of change scores of the OES and MEPI could be explained by the fact that the MEPI demonstrated significant ceiling effects from the first follow-up onwards. The ceiling effect does not allow to detect actual changes over time.There is no available literature concerning the validity of the OES and d before , 46. Then et al. . Change Quick-DASH (sub)scales were large (except moderate ES for Quick-DASH) suggests that both instruments display good to excellent ability to detect clinical change over time. Moderate to large ES and large SRM values have been shown before for the (Quick-)DASH or DASH [The finding that the standardized response mean (SRM) and effect size (ES) of the OES and  or DASH , 47–49.All instruments displayed a ceiling effect. This was as expected, since the type of elbow dislocations studied are relatively mild injuries, with expected full recovery within six months. Full recovery implies the largest score, and hence a ceiling effect. A similar phenomenon was also seen for the DASH in patients treated for a humeral shaft fracture . PatientThe interpretability represented by the MIC was 8.2 for the OES total score. The MIC for the OES pain, function and social-psychological subdomains  were lower than for patients who underwent elbow surgery for chronic elbow pathologies  as reported before . AlthougQuick-DASH was only 3.5 points. This is hard to believe for a scale that runs from 0 to 100, especially as previously published anchor-based MIC values for the (Quick-)DASH-score ranged from 8 to 19 points [Quick-DASH showed a ceiling effect, which implies that subtle impediments and changes cannot be measured from that point onward. This emphasizes the need for elbow-specific questionnaires like the OES for the less severe types of injuries. The OES also demonstrated a ceiling effect, however not before the six months follow-up moment, at which time patients were recovered to the largest degree.The MIC for the 9 points , 52–55. Quick-DASH the SDC was larger than the MIC. For the Quick-DASH, Polson et al. reported a SDC of 11, which was lower than 19 for the MIC [Ideally, the MIC should be larger than the smallest detectable change (SDC) in order to be able to differentiate between ‘real’ change and change caused by measurement error . For the the MIC . For theThe SEM in the current study was calculated with the corresponding change scores of patients that answered ‘no change’ on the transition item as a surrogate for test-retest values. This could have introduced some bias, which might have influenced the SDC value. Future studies should include an adequate test-retest analysis in order to be able to calculate a true SEM. Nevertheless, the anchor-based MIC values are the closest estimate of actual clinical change, therefore the MIC values in current study are of definite value.i.e., “completely recovered” and “worse than ever”) should be left out. Finally, there were insufficient data for evaluating whether the MIC values were the same for the consecutive time intervals.This study has some limitations. First, the relatively long time between the follow-up moments hindered an adequate test-retest analysis. Furthermore, it could also have led to recall bias with regard to the transition item. However, the interval for the transition item in the only other study that analyzed the MIC of the OES using an anchor-based approach was at least six months . SecondlStrengths of this study were its sample size and homogenous patient population. Furthermore, to the best of our knowledge, it is the first study to validate the OES for patients with elbow injuries treated non-operatively. Previous studies focused primarily on operated patients , 14, 23.Quick-DASH have proven to be reliable, valid, and responsive instruments for evaluating elbow-related quality of life in patients who sustained a simple elbow dislocation. Whereas validity of the OES was known for surgically treated chronic elbow pathologies, this study demonstrated the OES is also valid for acute elbow injuries treated non-operatively. Both instruments are useful for research purposes, and could play an important role in daily practice. The MIC and SDC values facilitate statistical power analysis and sample-size calculations for future clinical studies.The OES and S1 TableHypothesized correlations between the instruments for (A) construct validity and (B) Longitudinal validity in patients with a simple elbow dislocation.Expected strength of correlation or all possible combinations; r>0.6 indicates high correlation, 0.3<r>0.6 moderate correlation, and r> 0.6 low correlation.Quick-DASH, Quick disabilities of the arm, shoulder, and hand; BP, bodily pain; MCS, mental component summary; OES, Oxford elbow score; PCS, physical component summary; PF, physical functioning; SF-36, Short Form-36; US, utility score; VAS, visual analog scale.(PDF)Click here for additional data file.S2 TableData are shown as number with valid percentage.(PDF)Click here for additional data file.


Clinical and imaging data were obtained from the Cancer Imaging Archive. Forty-eight STS patients with FDG PET/CT and MR prior to therapy were analyzed. MTV of the tumor using MO-PET was compared to other conventional methods  and gradient-based method (PET Edge™). The reference volume was defined as an MR-based gross tumor volume (GTV). Spearman, intra-class correlation, and Bland-Altman analysis were performed to evaluate the correlation and agreement of MTV to GTV.We have previously developed a novel and highly consistent PET segmentation algorithm using a multi-level Otsu method (MO-PET). The aim of this study was to evaluate the reliability of MO-PET compared to conventional PET segmentation methods for measuring p < 0.05). MO-PET and PET Edge™ showed high intra-class correlation coefficient of MTV to GTV . The Bland-Altman bias results showed the highest agreement for MTV using MO-PET with GTV (26.0 ± 489.6 cm3) compared to other methods .MTVs obtained using each conventional SUV parameter, PET Edge™, and MO-PET were highly correlated with the GTV in Spearman and intra-class correlation analysis (max and absolute SUV threshold-based PET segmentation methods. MO-PET is comparable to PET Edge™. MO-PET is a reliable and consistent method for measuring tumor MTV.PET MTV segmented with MO-PET showed higher correlation and agreement with GTV in comparison to conventional percentage SUV Parameters including metabolic tumor volume (MTV) and total lesion glycolysis (TLG) began to emerge compensating the role of SUV [ cancers –5. Howevinterest . Also, irognosis , 8. Due e of SUV , 9, 10.max threshold method , and signal-to-background method [The definition of MTV, which is related to the distribution of metabolic activity, is the volume of hypermetabolic tissue that has metabolic activity exceeding a defined threshold . In orded method , 12. Howhttps://www.google.com/patents/WO2016160538A1?cl=en).Multi-level Otsu methods have been applied in several other application areas including in segmentation problems related to CT images. In the field of PET imaging, a variation of the basic Otsu method has been introduced as a solution to the PET segmentation problem . Howeveri given by Pi, the algorithm calculates the mean pixel level (μ) of the image and the inter-class variance (σ):Multi-level Otsu method, based on a more commonly known image threshold method known as Otsu’s method , is a siMean levelVariancei is an individual SUV value (within the SUV range), L is the maximum SUV level in a given image, and T1, T2, … TK-1 are multiple threshold levels that can potentially be computed in a given image based on the distribution of the SUV within the image or a region-of-interest. Multiple threshold level values are determined by exhaustively searching through all sets of threshold levels for the given number of classes (K) in to which the image needs to be divided to find the combination that gives the minimum within class variance (or maximum inter-class variance). Thus, ultimately, the algorithm generates K classes and K-1 thresholds for a given image.where In this research, MO-PET, an automatic algorithm requiring very minimal user-input, was used for measuring the MTV of soft tissue sarcoma. MTVs measured with MO-PET and other conventional methods were compared in order to evaluate the usefulness and robustness of MO-PET.http://www.cancerimagingarchive.net), an archive of medical images of cancer through the National Cancer Institute (NCI) [The clinical and imaging data were obtained from the Cancer Imaging Archive (TCIA: te (NCI) . TCIA iste (NCI) . Soft tite (NCI) , 20. Thihttps://imagej.nih.gov/ij/index.html), an image processing program developed by NIH. The plugin provided suitable support functions for reading and storing geometric contour information in RTSS data file format so that the contours can be exchanged between Mirada RTx and the plugin. One ellipsoidal volume of interest (VOI) containing primary tumor was drawn on each PET image. Various thresholds  were applied to one VOI and MTV for each threshold, termed as MTV (2.0), MTV (2.5), MTV (3.0), MTV (30%), MTV (40%), MTV (50%), or MTV (60%), respectively. MTV using MO-PET software (MTV (MO-PET)) was obtained using the identical VOI which was applied to the various threshold methods. For the reference standard volume, the tumor contours defined on the MRI were used. The MR contours, which were previously manually drawn on T2-weighted fat-suppression (T2FS) scans by Villiers et al., were obtained from the TCIA database [All PET/CT and MRI images were analyzed with Mirada RTx , with additional MO-PET segmentation algorithm developed and implemented as a plugin tool to use with ImageJ .max, and GTV are summarized in Table Fifty-one soft tissue sarcoma cases were obtained from the TCIA . Among tmax and absolute SUV threshold method-based PET segmentation did not perform well in comparison to GTV. Among the fixed percentage SUVmax threshold methods,  MTV (30%) showed the highest ratio of MTV to GTV (0.64 ± 0.35), while MTV (2.0) showed the highest ratio of MTV to the GTV (1.00 ± 0.61) among the absolute SUV threshold methods .The ratio of MTVs using each threshold and MO-PET to gross MR-based tumor volume (GTV) was calculated. MO-PET and the gradient-based method showed MTV to GTV ratio close to 1, at 1.12 ± 0.42 and 1.08 ± 0.38, respectively (Table max and absolute SUV threshold method-based PET segmentation did not perform as well in comparison. Spearman correlation coefficients (r) of MTVs using 30% SUVmax, 40% SUVmax, 50% SUVmax, 60% SUVmax, SUV 2.0, SUV 2.5, and SUV 3.0 to the reference GTV were 0.738, 0.621, 0.426, 0.291, 0.799, 0.680, and 0.561, respectively  showed comparable MTV, with the highest correlation to GTV. In addition, these two methods were superior to the absolute SUV and percentage SUVAs shown in the result, the calculated ratio of MTV (2.0) to GTV was most close to 1. However, the SD of MTV (MO-PET) ratio was smaller than that of MTV (2.0). Furthermore, the Spearman and intra-class correlation coefficients of MTV (MO-PET) were higher than that of MTV (2.0). According to the Bland-Altman analysis, the MTV (MO-PET) and MR-based tumor volume showed superior agreement to other methods.max threshold (30% SUVmax) showed greater discrepancy as the tumor volume increased. Furthermore, the absolute SUV threshold methods showed some limitation of tumor delineation, in cases where there were heterogeneous metabolic activities in the tumor [max, fixed percentage SUVmax threshold method may show underestimated MTV. Also, the MTV of the tumor which has low SUVmax may be undervalued with the absolute SUV threshold method. It was reported that the underestimation of MTV in the patients with low SUVmax would be possible [The Bland-Altman analysis showed that MTV(MO-PET) had strong correlation regardless of the tumor volume, while the tumor volume measured using absolute SUV threshold (SUV 2.0) or fixed percentage SUVhe tumor . In suchhe tumor . On the possible . The MO-In order to further evaluate MO-PET against commercially available software, PET Edge™ of MIM software was used to measure MTV. PET Edge™ measures MTV based on the gradient-based segmentation method . Spearmamax [max threshold method, lesion-to-background method, and gradient method for tumor segmentation which are used to measure MTV. MTVs depend on various threshold methods [Recently, MTVs are increasingly studied for the prediction of the prognosis of various cancers , 10, 11.max . Howevermax . It is d methods , 21. Man methods . Therefo methods . In addimax and other volume parameters including MTV and TLG are related to tumor prognosis [max is correlated with disease progression [max and MTV [Regarding soft tissue sarcoma that was analyzed in this study, several researches on the correlation between the PET parameters and tumor prognosis have been reported. However, the results reported have been conflicting with each other. For instance, it was reported in one study that there is positive correlation between the PET parameters (including SUV and other volume parameters) and metastasis . In anotrognosis . Whereasgression . Also, i and MTV . Due to There were two limitations in this study: (1) the reference standard volume was defined using the tumor contour on the MRI as an appropriate anatomic comparator for PET MTV; but MRI tumor contours are not necessarily a definitive reference standard. Also, there may be discrepancies between the volumes using the MRI contour with the actual pathologic volume; (2) the PET/CT images that were analyzed in this study do not have whole body images. So, lesion-to-background method cannot be compared in this study.max threshold and absolute SUV threshold-based PET segmentation methods. MO-PET is a reliable and consistent method for measuring tumor MTV. Quantitation of tumor metabolic burden using the MO-PET segmentation method shows very good assurance by its results for future clinical applications.In conclusion, PET MTV segmented with MO-PET method showed higher correlation and agreement with MRI-based GTV in comparison to conventional percentage SUV


Haemophilus influenzae on E. coli outer membrane. Also, a structure was designed according to Lpp-OmpA based on non-classical secretion pathway using bioinformatics software such as MEMSAT-SVM, ScrotumP and SignalP where it lacked any signal peptide at its N-terminal. Potential of this structure in the presentation of protein E on the surface of E. coli through non-classical pathway was indicated by western blotting, SDS page and fluorescent microscopy techniques, similarly its effectiveness was compared with Lpp-OmpA system. The results of the current study showed that the new structure had higher efficiency than Lpp-OmpA, and it could transport protein E on outer membrane well. This study is the first report in the presentation of H. influenzae PE onto the surface of E. coli by Lpp-OmpA, and the structure originated from Lpp-OmpA, according to the non-classical secretion pathway. Our results suggest that non-classical secretion pathway may be exploited as a new secretory pathway on the outer surface of the cell for recombinant proteins.Today, transference of recombinant protein on the outer surface of bacteria is deemed as a valuable process for various applications in biotechnology including preparation of vaccines. In this study, Lpp-OmpA structure was used to present outer membrane protein E of The online version of this article (doi:10.1186/s13568-017-0350-0) contains supplementary material, which is available to authorized users. Haemophilus influenzae is a significant pathogen that is categorized into two different main groups predicated on the presentation of a polysaccharide capsule. Encapsulated H. influenzae has been classified to six various serotypes (a–f), the large number of them are the reason to invasive sickness, and the nonencapsulated H. influenzaee has been determined nontypeable H. influenzaee (NTHi), are considered as accountable for the preponderance of mucosal Haemophilus putridity and infections in the respiratory tract  has been specified to act as an active place for the interplay with epithelial cells  attached to a transmembrane domain (amino acids 46–159) from outer membrane protein A (OmpA)  devoid of Lpp and any signal peptide with protein E termed Non-OmpA-PE. Also, this chimeric protein is aimed and joined to E. coli outer cell surface and contrasted its surface targeting efficiency with the Lpp-OmpA system.Some bacterial proteins have been observed to be secreted without any apparent signal peptide. In this system, known as non-classical secretion, protein secretion does not depend on any of the five recognized secretion pathways (type I–V) in Gram-negative bacteria  and X-factor (hemin-l-histidine) in a humid atmosphere containing 5% CO2. E. coli Dh5α was employed as a recombinant host for sub cloning and plasmid manipulation, while E. coli strain BL21 (DE3) was served as a host for gene expression and surface display of Lpp-OmpA-PE and Non-OmpA-PE. Recombinant cells were grown in Luria–Bertani media at 37 °C supplemented with 50 µg/ml kanamycin.All strains, plasmids and primers used in this study are listed in Table http://www.cbs.dtu.dk/services/SignalP) and LipoP . The first 70 amino acids of N-terminal of each protein were examined in both of the signal peptide predictions. SecretomeP was used for Prediction of non-classical protein secretion (http://www.cbs.dtu.dk/services/SecretomeP). TopPred program a topology prediction of membrane proteins (Claros and von Heijne http://bioinf.cs.ucl.ac.uk/psipred).To predict the presentation of the signal peptides, we have tested the sequences using two well-known neural network-based programs, including, SignalP  was amplified using PCR with primers NcoIpE22 and PEHindIII and then digested by NcoI and HindIII. The insert was ligated into pET-26b that had been digested with similarly enzymes to produce pPE22-160. To create pLpp-OmpA-PE, the pe (aa 22-160) was PCR amplified from Haemophilus influenzae genome using primers EcoRIpE22 and PEHindIII and digested with EcoRI and HindIII, then ligated into similarly digested pLpp-OmpA. To construct a non-classical plasmid for the expression of the Non-OmpA intracellularly, the ompA gene without signal peptide was PCR amplified from E. coli genome using primers NonOmpAF and NonOmpAR. The PCR product was digested with NdeI and EcoRI and then ligated into similarly digested pET-26bto generate pNon-OmpA. The pe gene already was PCR amplified and digested with EcoRI and HindIII ligated into similarly digested pNon-OmpAto produce pNon-OmpA-PE. The recombinant plasmids were sequenced to confirm the correct sequence of the inserted genes. Transformation of the plasmid into E. coli Dh5a was carried out using the CaCl2-mediated transformation , incubated for 1 h on ice and disrupted by sonication  was resuspended sterilized distilled water. To isolate the inner and outer membranes, N-lauryl sarcosyl was added to the pellet  and was incubated at room temperature and then centrifuged at 15,000×g for 30 min. The supernatant was utilized as the inner membrane fraction after dialysis, and it was concentrated by precipitation and the insoluble pellets were resuspended in 20 ml of the 2% SDS buffer as outer membrane protein, and analyzed by using 15% SDS–polyacrylamide gel electrophoresis  at a final 1:1000 dilution in phosphate-buffered saline (PBS) buffer and secondary goat anti-rabbit horseradish peroxidase (Biolegend), at a final 1:2000 dilution in PBS buffer (Sambrook and Russell g for 4 min and washed three times with PBS (pH 7.4) supplemented with 3% bovine serum albumin. In the next step, the cells were incubated with the rabbit anti-6His antibody diluted 1:1000 in PBS solution for 1 h at 4 °C. After washing five times with PBS, the cell-antibody complex was incubated 1.5 h at 4 °C with a goat anti-rabbit IgG conjugated with FITC  at a dilution of 1:500. For microscopic observation, cells were washed five times with PBS solution to remove unbound anti-6His-FITC antibody, then mounted on microscopic slides and was observed by fluorescence microscopy.Immunofluorescence microscopy was used to investigate the presentation of recombinant proteins on surface display. A 250 µl of recombinant cells harboring Lpp-OmpA-PE and Non-OmpA-PE were harvested and centrifuged at 3500×Hemophilus influenzae. They were analyzed of the secretion capability and transition systems by SignalP and LipoP and SecretomeP software. The bacterial localization was assessed by PSORTb v3.0.2 and the secondary structure and transmembrane helixes were predicted by PRED-TMBB and PSIPRED servers, respectively. Genscrips have done the analysis of negative cis elements and sequences repetition  was used to create a novel construction and was compared with Lapp-OmpA and were joined to protein E from E. coli. Therefore, the fusions containing Lpp-OmpA-PE and Non-OmpA-PE have been analyzed by SecretomeP. Non-OmpA-PE indicated high validity on the non-classical pathway  were considered singly by SignalP, LipoP, and SecretomeP. The results indicate capability of them in applying the non-classical pathway for secretion to the surface of 2–160 weray Figs. , 4. PSORThe construction was developed on merit to keep the original OmpA aa 46–159) and elimination of Lpp, its signal peptide and addition of nine amino acids to its beginning. Afterward, it joined to PE 22–160 by a linker was located between them. The recombinant plasmids was proved by restriction enzyme digestions, analysis on the agarose gel and DNA sequencing. The expression of the chimeric proteins under the control of the T7 promoter and induction by isopropyl-beta-D-thiogalactopyranoside (IPTG) were confirmed by SDS-PAG and Western blotting with specific anti-6His tag antibody. The expressed recombinant proteins of pLpp-OmpA, pNon-OmpA, pPE, pPE22-160, pLpp-OmpA-PE and pNon-OmpA-PE plasmids were about 16, 23 and 30 kDa, respectively. The results are shown in Fig. 9 and eliTo confirm the occurrence of recombinant proteins on the outer membrane, the membrane and soluble fractions were separated and used for SDS-PAGE analysis. The presence of chimeric proteins were illustrated in cytoplasmic and outer membrane fractions. Specific bands corresponding to 30 kDa fusion proteins were successfully detected in the total protein extracts as well as the outer membrane fractions from cells harboring the plasmids pLpp-OmA-PE, and pNon-OmpA-PE. There was no detected signal in non-induced cells Figs. , 6b. TheE. coli straightly certified by immunofluorescence staining. An indirect immunofluorescent antibody technique was used to detect surface display on the recombinant host. After fixation, the primary rabbit anti-6His and the secondary goat anti-rabbit FITC antibodies were applied to stain the surface of the E. coli. Non-induced E. coli cells were employed as a negative control. As mentioned in Fig. E. coli recombinant strains express the fusion proteins. The cells harboring Non-OmpA-PE and Lpp-OmpA-PE constructs display Non-OmpA-PE and Lpp-OmpA-PE fusion proteins respectively, while, both the expression and display of fusion protein was augmented in Non-OmpA-PE plasmid harboring cells. Wild-type E. coli cells were non-induced by IPTG not showing recombinant proteins on their surface and no fluorescence  and protein E from H. influenzae were deleted and the potential capacity of each protein for non-classical pathway utilization were analyzed by bioinformatics programs. As the result the capacity did not altered significantly. According to further analysis, fusion of OmpA (aa 46–159) without Lpp and lack any signal peptide with protein E (aa 22–160) from H. influenzae, increase the NN sequences core scores of non-classical prediction from 0.43 to 0.96. Based on output of SecretomeP, the secreted proteins of non-classical pathway should acquire an NN-score and SecP score exceeding the threshold about 0.5 for bacterial sequences. But at the same time presentation of a signal peptide shouldn’t be predicted by SignalP. It indicates that the fusion has non-classical secretory potential. Recent studies determined a hydrophobic helix domain (aa 108–126) of enolase N-terminal that might be essential for its secretion, come to the result that the hydrophobic helix domain might be vital for enolase secretion by the non-classical pathway in E. coli as in B. subtilis (Yang et al. Protein E is an outer membrane protein discovered in both encapsulated H. influenzae, PE immunization motifs in region 84-108 are available outside the cellular membrane. In this case, it may show high immunization potential and makes it as an appropriate candidate for the vaccine (Ronander et al. The results of TMRPres2D software indicate that this structure is properly embedded in the membrane and at the same time similar to case it occurs in A high transcription rate may inhibit the surface display of a recombinant protein as translocation is the restriction step (Rodrigue et al. E. coli via vesicles that stem from the outer membrane. The ClyA is secreted independently from the five known secretion pathways in Gram-negative bacteria. Thus to achieve the hydrophobic helix, the comparison of Non-OmpA with ClyA in the N-terminal region sequences revealed hydrophobic helix in N-terminal of both structures. It signifies that this domain may be necessary for this pathway (Fig. ClyA, a porous protein shows a cytotoxic effect on mammalian cells, transports without any N-terminal signal peptide, at the same time is released from way Fig.  (Ludwig way Fig. .E. coli outer membrane. Also, it may essentially contribute to our perception of quality of function of non-classical secretion pathway.These results indicate that the designated structure has the suitable potential for expression of recombinant proteins particularly heterologous membrane proteins onto Briefly, in this survey, Non-OmpA derived from Lpp-OmpA, was employed to display protein E on the cell surface. Non-OmpA was designated for secretion to outer membrane by bioinformatics tools through the non-classical pathway. This research indicates that Non-OmpA is indeed efficient for displaying the recombinant proteins, and it can be assumed as a target in vaccine-related research.